class_docstr: Bridge class to connect langchain.embeddings module to mindsDB
class_docstr_tok: ["Bridge","class","to","connect","langchain.embeddings","module","to","mindsDB"]
code: def __init__(self, model_storage, engine_storage, **kwargs) -> None:
      super().__init__(model_storage, engine_storage, **kwargs)
      self.generative = True
  
file_path: mindsdb/mindsdb/integrations/handlers/langchain_embedding_handler/langchain_embedding_handler.py
imports: import copy
  import importlib
  from typing import Dict, Union
  import pandas
  from langchain.embeddings.base import Embeddings
  from pandas import DataFrame
  from mindsdb.integrations.libs.base import BaseMLEngine
  from mindsdb.utilities import log
label_desc: Use image node_id 1 to create a new LangchainEmbeddingHandler object from inherited base classes: BaseMLEngine with example: obj = LangchainEmbeddingHandler(model_storage, engine_storage)